A Graphical Game Approach to Electrical Vehicle Charging Scheduling: Correlated Equilibrium and Latency Minimization

Chunlei Sun, Xiangming Wen, Zhaoming Lu, Junshan Zhang, Xi Chen

Research output: Contribution to journalArticlepeer-review

Abstract

Electric vehicles (EVs) are becoming increasingly popular, but the frequent charging and large charging latency remain major obstacles to the EV industry. This article focuses on the charging scheduling of on-the-move EVs in a transportation network to minimize EVs' charging latency, including driving time to charging stations (CSs), wait time and charging time. We formulate this charging scheduling problem as a graphical game to characterize the strong couplings of charging latency among neighboring EV players. Specially, we investigate correlated equilibrium (CE) to describe the joint strategies of EV players, which is expected to further reduce the charging latency of EVs compared with Nash equilibrium (NE). It is shown that CE always exists in a finite game, and can be found by linear programming tools. In addition, we propose a method of wait time prediction, which can improve the prediction accuracy by combining the data of deterministic EV arrivals and the stochastic property of potential EV arrivals. Simulation studies are used to examine the performance of the proposed game-based approach, the efficiency of CE, the preciseness of our proposed wait time prediction method, the impacts of CS deployment on EVs' charging latency, etc. We can draw a conclusion that our method has apparent advantages in situations where the locations of EV players are in dense manners.

Original languageEnglish (US)
Article number9216526
Pages (from-to)505-517
Number of pages13
JournalIEEE Transactions on Intelligent Transportation Systems
Volume22
Issue number1
DOIs
StatePublished - Jan 2021

Keywords

  • Electric vehicle
  • charging latency
  • charging scheduling
  • correlated equilibrium
  • graphical game

ASJC Scopus subject areas

  • Automotive Engineering
  • Mechanical Engineering
  • Computer Science Applications

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